# LFM3-1.7B vs Qwen3.5-122B-A10B (slim)

> Qwen3.5-122B-A10B scores 63.1 (B) to LFM3-1.7B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-122b-a10b.md (~9,700 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-122b-a10b.json · canonical https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-122b-a10b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Qwen3.5-122B-A10B scores 63.1 (B) on agent readiness against LFM3-1.7B's 61 (C), and leads in 1 of 4 scored categories. LFM3-1.7B leads on reach, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- LFM3-1.7B: C 61, rank #69 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-1-7b.min.md
- Qwen3.5-122B-A10B: B 63.1, rank #25 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-122b-a10b.min.md
- LFM3-1.7B, good for Agents on a laptop, phone or small server that need tool calling and a long context from a model under 2 GB at 4 bits Ahead on Reach, 85 against 80; Agent interface, 100 against 70; Documentation and upkeep, 67 against 34.
- Qwen3.5-122B-A10B, good for Agents with a 128 GB unified-memory machine or two large GPUs that want a capable vision-language model with a plain licence. Ahead on Risk, 55 against 40.

| Category | LFM3-1.7B | Qwen3.5-122B-A10B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 80 |
| Risk (20%) | 40 | 55 |
| Agent interface (10%) | 100 | 70 |
| Documentation and upkeep (10%) | 67 | 34 |

| Fact (where they differ) | LFM3-1.7B | Qwen3.5-122B-A10B |
| --- | --- | --- |
| Vendor | Liquid AI | Alibaba (Qwen team) |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 |
| llms.txt | yes | no |
| Last release | 2026-11-09 | 2026-02-24 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Documentation and upkeep, LFM3-1.7B +33: LFM3-1.7B 67 (Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), a limitation (not recommended for agentic coding or complex multi-ste…); Qwen3.5-122B-A10B 34 (The card covers five of the seven items and misses limitations and a cut-off (14).)
- Agent interface, LFM3-1.7B +30: LFM3-1.7B 100 (Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, tools, deferred tools, tool results and the thinking switch.); Qwen3.5-122B-A10B 70 (The template ships in the repository (20) and renders several tool calls per turn for a model trained for tool use (20).)
- Risk, Qwen3.5-122B-A10B +15: LFM3-1.7B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Qwen3.5-122B-A10B 55 (Safetensors only with no repository code run on load or to build prompts gives file safety 25, and files in the Qwen organisation the publisher's GitHub links t…)
- Reach, LFM3-1.7B +5: LFM3-1.7B 85 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB, and 1.10 GB × 1.2 = 1.3 GB, which fits 8 GB, well inside the 16 GB line.); Qwen3.5-122B-A10B 80 (Memory earns 10 of 30, since Alibaba's GPTQ 4-bit build is 78.9 GB, about 95 GB with a fifth added, which fits our reference machine but no smaller band.)